It is known that spectral distribution of an image of an object picked up with an image sensor can be expressed as a product of spectral radiance of a light source and spectral reflectivity of the object itself, and it is publicly known that a picked up image is affected by the light source. Therefore, in order to perform white balance processing for achieving the same balance of color under any light source or color isolation processing (color matrix processing) for correcting pixel mixture, light source information of an object to be shot is required. Further, also in the case where an image is corrected through digital processing for color shading occurring depending on a light source, light source information of an object to be shot is required.
When light source information required for such processing is acquired through automatic estimation, in order to achieve higher image quality of a picked up image through the image processing, it is important to perform light source estimation with high accuracy.
Conventionally, a light source estimating apparatus has been proposed which calculates a sensitivity ratio between an R pixel and a B pixel, and a sensitivity ratio between a B pixel and a G pixel and estimates a light source from correlation between these sensitivity ratios and a sensitivity ratio of a reference light source. However, with the above-described apparatus, influence of spectral spatial characteristics of an object itself is significant. Therefore, when there is deviation in color of an object, for example, when the whole screen is uniformly red, there is a problem that it is difficult to distinguish whether the object itself is red or the object looks red due to influence of the light source, which degrades accuracy of light source estimation.